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December 1, 2005

The 2005 ‘Fiscies’: The Best and Worst in Connecticut Fiscal Policy

Yankee Staff Budget, Economy, Taxes Connecticut Post’s Linda Conner Lambeck, East Windsor Board of Finance Chairman Paul Catino, enemy of the taxpayer, friend of the taxpayer, governor Jodi Rell, Hartford Courant’s Christopher Keating, Hartford Courant’s Robert Frahm, Middletown Mayor Domenique S. Thornton, Save Westbrook, State Rep. Kevin DelGobbo, State Senate President Donald E. Williams, Tax & Budget, The News-Times’s Elizabeth FitzGerald 0 Comments

December 2005

With the highest local-state-federal tax burden and one of the most ravenous spending habits in the nation, fiscal policy in Connecticut is disturbingly irresponsible — particularly given the state’s fragile economic health. Unfortunately, 2005 was a year that saw the Nutmeg State’s addiction to Big Government worsen. Tax hikes and spending increases were commonplace.

On the bright side, the grassroots rebellion against Connecticut’s excessive property-tax rates intensified in 2005. This resistance was surely a factor in November’s municipal elections, which saw a large number of incumbents thrown out of office.

Herewith, the Yankee Institute for Public Policy presents its awards for the best and worst in 2005 Connecticut fiscal policy.

ENEMY OF THE TAXPAYER, STATE

For signing a big-spending, tax-hiking budget for the 2005-06 fiscal year, the Yankee Institute gives its state-level “Enemy of the Taxpayer” award to Connecticut Governor M. Jodi Rell.

During the 2005 legislative session, the governor demonstrated no willingness to confront Connecticut’s longstanding fiscal problems. Instead, she embraced both higher spending and higher taxes.

Spending was boosted by a jaw-dropping 8.7 percent. And taxes raised/imposed on Connecticut’s beleaguered families included:

* a massive hike in the state’s tax on petroleum products — at a time when gasoline prices are sky-high

* a new death tax that encourages retirees to flee the state

* a reduction in the property-tax credit available to citizens with an income-tax obligation

* a new nursing-home tax — imposed as part of a complicated and misguided scheme to obtain more federal funding — that raises the state’s eldercare costs (which are already the highest in the nation)

While the legislature bears much of the blame for the 2005-06 budget — and deserves an honorable mention in this category — only the governor had the power of a statewide bully pulpit to stand up to tax hikes and runaway spending, and explain to voters why fiscal changes are badly needed. Unfortunately, Rell chose to continue the state’s unsustainable tax and spending habits.

ENEMY OF THE TAXPAYER, LOCAL

For inept management of their city’s high-school building project, former Middletown Mayor Domenique S. Thornton and the members of the Middletown High School and Vo-Ag Center Building Committee earn the Yankee Institute’s “Enemy of the Taxpayer” award at the local level.

Middletown’s new high school has been a debacle from the start. In 2003, the building committee named TBI Construction Company its construction manager, despite the firm’s involvement in the scandals that ultimately put former Governor John Rowland in federal prison. In January 2004, Middletown officials signed a “project labor agreement” with construction unions that limited competitive bidding and all but guaranteed a higher cost to taxpayers. In April 2004, Middletown’s Inland Wetlands and Watercourses Agency denied the school a permit for environmental reasons. (Five months later, a modified version of the project won approval.)

The latest blow to the troubled project struck this summer, when sealed bids for the high school were opened. Estimates were many millions of dollars more than the amount voters approved in 2003. Now the often-modified project faces even more redesign work, and it is all but certain that taxpayers will be asked to approve additional funding in 2006. There is reason for optimism, though: The city’s new mayor has pledged to abandon the project labor agreement and recently appointed new members to the building committee.

The cost overrun of Middletown’s new high school should come as no surprise. All over the state, school-construction projects are behind schedule and over budget. Unfortunately, these fiscal follies at the local level don’t just impact citizens with property-tax obligations. State revenues cover large percentages of school-construction projects, and thus every taxpayer in Connecticut is affected. School-choice alternatives are needed more than ever in the Nutmeg State.

FRIEND OF THE TAXPAYER, STATE State Rep. Kevin DelGobbo earns Yankee’s “Friend of the Taxpayer” award at the state level.

During the legislative session, he lobbied for a bill that would have finally enacted the state’s spending cap — a measure overwhelmingly approved by voters in 1992. As DelGobbo explained in January, “successive legislatures have purposefully ignored and thwarted the will of Connecticut voters by failing to adopt the cap as a constitutional provision.” The bill was referred to the Appropriations Committee, but was not even given a public hearing, much less a vote.

In September, DelGobbo proposed suspending the newly enacted hike in Connecticut’s petroleum-products tax. “The one thing state lawmakers can do right now is stop adding to the pain of high gas prices by rolling back the tax they dramatically increased this year,” DelGobbo told the Journal Inquirer. (Not surprisingly, legislators and the governor saw things differently, and ignored his request.)

For his commitment to spending restraint and tax relief, DelGobbo was truly a friend of Connecticut taxpayers in 2005.

FRIEND OF THE TAXPAYER, LOCAL

Save Westbrook, a taxpayer group fighting for fiscal responsibility in its town, is awarded the “Friend of the Taxpayer” award at the local level.

Westbrook has not approved a budget for the 2005-06 fiscal year — the only Connecticut municipality yet to do so. That’s largely due to the gutsy and indefatigable efforts of Save Westbrook. So far, the shoreline town has defeated four budgets, mostly in response to municipal officials’ refusal to make the cuts clearly needed to satisfy a majority of voters. Financial research and get-out-the-vote efforts by Save Westbrook have clearly had an impact.

QUOTE OF THE YEAR, STATE

“Having the millionaire’s tax reserved for a time when we hit a very rough patch in the state’s future is really a very good thing.”

In June, State Senate President Donald E. Williams explained to The Day that while hiking the state’s income tax wouldn’t happen this year, he took comfort in the fact that it was still available for future implementation.

Research has shown that steeply “progressive” state income-tax rates are associated with poor economic growth, and that raising taxes during an economic downturn is one of the most harmful things a state government can do. Williams and the powerful lobbying machine that continues to press for higher Connecticut income-tax rates continue to deny this research, in their never-ending quest for more tax revenue to spend.

QUOTE OF THE YEAR, LOCAL

“That kind of stuff I’m not interested in.”

That’s what East Windsor Board of Finance Chairman Paul Catino had to say in May, after a reporter asked him why town voters defeated a 9.3 percent hike in their property tax rate. East Windsor’s concerned taxpayers mounted a true grassroots effort to defeat the tax hike, and went on to defeat two more budgets before adopting a 2005-06 spending plan in July.

The Hartford County town was just one of dozens around the state that rejected — often by wide margins, and often more than once — tax-hiking budgets. While some municipal officials are sensitive to voter outrage over ever-higher property taxes, Catino’s comments demonstrate that all too many remain indifferent to the plight of local taxpayers.

BEST MEDIA COVERAGE

The Hartford Courant’s Christopher Keating has consistently shown a sophisticated understanding of fiscal policy in Connecticut. Not all his writing has measured up, but on several occasions in 2005 Keating demonstrated a grasp of tax and spending policies that too many of his colleagues sorely lack.

In April, Keating wrote a revealing article on the role healthcare costs (Medicaid and coverage of state employees) play in driving state budget growth. In August, he described how “legislative leaders have steered the award of [bond commission] grants for the political benefit of members, who can then claim credit with voters in their districts.” In October, Keating reported the outrage over the governor’s new death tax, and even allowed critics to suggest that by driving the state’s more affluent residents away, projections about the revenue the tax will raise might not pan out.

For these articles, Keating deserves the award for best media coverage of 2005.

WORST MEDIA COVERAGE

For their failure to objectively scrutinize the claims of the Connecticut Coalition for Justice in Education Funding (CCJEF), Connecticut’s education reporters — particularly the Hartford Courant’s Robert Frahm, the Connecticut Post’s Linda Conner Lambeck, and The News-Times’s Elizabeth FitzGerald — collectively earn the award for worst media coverage of 2005.

Time and time again, researchers have failed to find a connection between higher school expenditures and improved student achievement. The Texas Supreme Court recently rejected an attempt to boost school spending in the Lone Star State, concluding that “more money does not guarantee better schools or more educated students.” (One justice suggested that “more competition” would help government schools the most.)

But try telling that to Connecticut’s education reporters, who consistently fail to question the inaccurate assertions of the state’s government-school lobby. While sound bites from skeptics sporadically appear in education-funding articles, for the most part reporters serve as press agents for the teacher unions and politicians who relentlessly push for more spending on the Nutmeg State’s government schools.

Media coverage of the filing of CCJEF’s “education equity” lawsuit in November was particularly one-sided. Puff profiles of plaintiffs and talking points from the organization’s officials were the norm — not hard-hitting analysis of the questionable “research” behind the lawsuit. Theresa McGrath, the Yankee Institute’s education specialist, calls CCJEF an attempt to “legally coerce a failed policy.” However, the state’s education reporters ignored this argument, and chose to act as conduits for the costly myth that more school spending will boost student performance. They also continue to ignore the school-choice movement that is revolutionizing education in other states.

May 3, 2005

Fiscal Focus – Connecticut’s Tax Burden: An Overview

Yankee Staff Policy Brief 0 Comments

May 3, 2005
ALL TAXES: THE HIGHEST BURDEN IN THE NATION
Connecticut’s residents bear an incredibly high burden of taxation at the local, state, and federal levels. As a share of personal income, the total tax bite in Connecticut in 2005 is 33.5 percent. This burden makes Connecticut the most heavily taxed state in the nation.1
In 2005, Connecticut’s “Tax Freedom Day”—the date at which residents stop working for the public sector and start earning money they can keep for themselves— falls on May 3.2
FEDERAL TAXES: A RETURN OF 65¢ ON THE DOLLAR
Connecticut receives a very poor return on the tax dollars it sends to Washington, D.C. According to the Edward J. Bloustein School of Planning and Public Policy at Rutgers University, only 65¢ comes back to the state in spending for every dollar that residents send to the federal treasury. Only one state, New Jersey, fares worse.3
According to research by the Tax Foundation, Connecticut’s return on its federal tax obligation has actually declined in recent years.4
Apparently, Governor Rell’s budget director is satisfied with this arrangement. “We send a lot more money to Washington than we get back … and that’s how it ought to be,” Robert Genuario recently told The Advocate.5
STATE TAXES:                                                                                                                                                                                 FROM $0 TO $4 BILLION—AND THAT’S JUST THE INCOME TAX
Connecticut’s income tax, which did not exist 14 years ago, now extracts over $4 billion each year from Nutmeg State residents.6
The state’s income tax almost certainly contributed to Connecticut’s sluggish economy in the 1990s. In that decade, the Nutmeg State ranked 47th in population growth, 41st in inflation-adjusted income growth, and 50th in job creation.7
At 6 percent, Connecticut’s sales tax is more burdensome, as a percentage of personal income, than the national average.8
Connecticut’s corporate tax is 7.5 percent, the national average.9 Yet it generates only 4 percent of all state revenue. According to the Cato Institute’s Chris Edwards, “State corporate income taxes might be the most inefficient taxes in the nation, because they create large burdens on businesses but raise little revenue.”10
Drivers in the Nutmeg State pay a gasoline tax of 25¢ per gallon, but Connecticut’s gross receipts tax, which usually is assessed by a wholesale oil company, adds an estimated 10¢ per gallon to the total cost.11
Connecticut’s taxes on beer, wine, and distilled spirits are generally higher than those in other states.12
At $1.51 per pack, Connecticut’s cigarette tax is among the highest in the nation.13
LOCAL TAXES: ONE OF THE HIGHEST PROPERTY-TAX BURDENS
Connecticut’s citizens “work longer to pay their local property tax than any other state tax; and longer than local property taxpayers in all other states but four.”14 Property taxes consume over one third of a taxpayer’s combined state-local tax burden.15
There are now over 50 local taxpayer organizations in Connecticut.16 These groups are growing increasingly influential. In 2004, for the first time ever, a majority of town budgets that went to referendum were defeated.17
Notes:
1. Comparative state data can be found at www.taxfoundation.org/statelocal.html.                                                             2. Tax Freedom Day data can be found at www.taxfoundation.org/taxfreedomday.html.                                                   3. Pam Dawkins, “State plays cash cow for federal government, gets little back,” The Connecticut Post, October 28, 2004.                                                                                                                                                                                                        4. Federal taxation/spending ratios can be found at www.taxfoundation.org/taxingspending.html.                               5. Tobin A. Coleman, “Legislative panel backs Genuario for budget post,” The Advocate, January 19, 2005.                 6. D. Dowd Muska, “State’s overlooked tax burden,” The Connecticut Post, September 5, 2004.                                       7. Steve Moore, “States Can’t Tax Their Way Back To Prosperity: Lessons Learned from the 1990-91 Recession,” American Legislative Exchange Council, October 2002.                                                                                                              8. “Economic Report of the Governor,” February 4, 2004.                                                                                                         9. Ibid.                                                                                                                                                                                                    10. Chris Edwards, “Golden Opportunity for Every State,” Investor’s Business Daily, January 27, 2004.                     11. Estimate by the Independent Connecticut Petroleum Association, www.icpa.org.                                                         12. “Economic Report of the Governor,” February 4, 2004.                                                                                                       13. Ibid.                                                                                                                                                                                                  14. Connecticut Conference of Municipalities press release, May 29, 2002.                                                                         15. Don Klepper-Smith, “Connecticut’s Current State-Local Tax System: A Comparative Analysis,” September 27, 2002.                                                                                                                                                                                                      16. Yankee Institute estimate.                                                                                                                                                          17. Federation of Connecticut Taxpayer Organizations estimate.

October 1, 2004

The Early Graduation Reward Plan: Helping High School Students Mature While Municipalities Reduce Spending

Yankee Staff Policy Brief 0 Comments

Lewis M. Andrews, Ph.D.
For references and tables outlining savings from early graduation see PDF attachment at the bottom of the page.
Executive Summary
While there is no such thing as a “free lunch,” the simple reform of encouraging high school students to graduate in three years by rewarding those who do so voluntarily with a college scholarship would achieve the following:
1. … improve the academic quality of public education;
2. … reduce the skyrocketing state and local taxes required to fund public education;
3. … attenuate the boredom that drives adolescents to engage in self-destructive behavior, especially drug abuse and promiscuity;
4. … make higher education more affordable for all students, but especially those from poor and middle class families;
5. … give adolescents who desire it the option once enjoyed by previous generations to “take some time off” from the education-career path and try something different;
6. … relieve growing towns and cities from the crushing burden of costly new school construction;
7. … bring the defenders of the current public education system and its critics together in the common cause of helping future generations.

Background
The idea of allowing high school students to graduate in less than four years is not new. Leon Botstein, the distinguished president of Bard College, has long argued that the current curriculum of American high schools is a hindrance to academic achievement with the worst damage wreaked on average and below-average pupils. Indeed, Bard has become an elite college in part by deliberately admitting many secondary students after their junior year in high school.
If the notion of eliminating a grade for a sizeable number of students is not new, neither does it turn out to be very difficult. This is because most school districts in North America define graduation requirements, not by years attended, but by the completion of certain required courses. Since high school students are permitted many electives over the course of four years, condensing the curriculum into three grades is largely a matter of students substituting required courses for some electives.
In 2003, the province of Ontario eliminated an entire grade with the only apparent problem being an unusually large number of applicants to Canadian colleges and universities in one year. Also in 2003, Gov. Jeb Bush instituted a voluntary three-grade curriculum for all of Florida’s schools. Any Florida student who elects a “fast track” to high school graduation now has the right to pursue it as long as he or she takes all the state’s required courses. On the other hand, there is no compulsion to give up the senior year, and students on the accelerated path have at least one opportunity every year to step off it.
Indeed, in most states the requirements for high school graduation are so flexibly written that the majority of America’s local school boards already have the authority to confer diplomas on those who finish before the end of four academic years. In Connecticut, many towns have debated, adopted, reconsidered, and revised their own early graduation policies. Ridgefield, for example, offers a three-and-a-half-year curriculum, allowing seniors to finish in February. West Hartford’s Public School Administrative Regulations for Graduation acknowledge that “there are students capable of graduating from high school in three years” but require a formal application that must be approved by teachers, guidance counselors, the high school principal, and the superintendent. Middletown, on the other hand, has a streamlined process, which allows the student’s building principal to approve early graduation as long as the request is made at least one semester prior to the desired date. Westport’s Staples High School and the Lewis Mills High School in Burlington also facilitate early graduation.
Interestingly, the idea of encouraging early graduation is a reform that has the potential to unite political divisions. In his book Jefferson’s Children, Botstein makes it clear that he is a long-time liberal opposed to many conservative education reforms, such as vouchers, tax credits, and the public subsidy of private and parochial secondary schools. Gov. Bush, on the other hand, has pioneered many of these very same reforms. It seems clear that finding ways to encourage early graduation could heal communities currently divided over the exploding cost of secondary education and unite them in the common cause of helping future generations.

A New Twist
The proposal made here would increase the frequency of early graduation by employing a financial incentive that would greatly benefit both students and taxpayers. Specifically, it is recommended that students who graduate early be granted a college scholarship equal to one third of the high school’s annual per pupil cost. At a time when this number for many Connecticut high schools is rapidly approaching $15,000, such a policy could translate into a $5,000 student scholarship and a $10,000 rebate to property taxpayers, as well as to state income and sales taxpayers (who subsidize secondary education in some towns and cities through the mechanism of Education Cost Sharing).
Under this recommended plan, a higher sum is rebated to taxpayers (than to students) for two reasons. First, some school districts will want to reserve part of the taxpayer rebate to cover the fixed costs of maintaining a high school that would not necessarily be reduced by lowering the senior census through early graduation. As the definition of a high school’s fixed costs is potentially a debatable issue until the plan is actually implemented by a given school board, the relatively higher rebate to taxpayers ensures that there will be more than enough funds to reduce the education budget, even after a generous reserve for building maintenance. Once a high school’s administrators and its governing board become more comfortable with the financial benefits of early graduation, the scholarship amount can always be raised.
Second, as we shall see, a $5,000 scholarship can be used by graduating students to fill the inevitable gaps in the financial aid packages offered by the vast majority of private and public colleges.
Let us proceed to examine in greater detail each of the benefits of a senior year, early graduation reward policy:
1. Improve the Overall Quality of Public Education
The structure of public education as we practice it today is an invention of the late eighteenth century, a time when factory owners cared little for employee morale … when family harmony meant physically punishing a disobedient child or wife … and when seriously sick people got better care in their homes than in hospitals. Things have certainly improved for factory workers, family members, and hospital patients; but what about for students? A quirk in the design of teacher colleges in America — whereby future educators are trained, not to master a field (math, English, history, biology) but an age group (elementary school, middle school, high school) — has led many people to mistakenly conclude that the surviving organization of public education is both natural and appropriate.
Yet, when we step back and look at public education objectively, we make a surprising discovery. Americans are so accustomed to hearing that their schools are inferior compared to those of the Japanese and the Europeans that they have missed an important fact. If we were only comparing American children in grades K-to-4 th grade with their foreign counterparts, we would be surprised to learn that students in the United States do quite well when measured against their contemporaries abroad. Indeed, according to federal monitoring, the math and science skills of the typical American nine-year-old have actually improved considerably since the late 1960s. It is only during the middle school, and particularly the high school, years when our educational process begins to break down.
“The weakest part of America’s educational system is located at the juncture between adolescence and schooling,” says Bard’s Botstein. “For all income classes, races, and regions, the … years from ages twelve and thirteen to seventeen and eighteen mark a time of trouble …. The traditional high school is an out-of-date strategy and system. In terms of its curriculum, it remains a useless middle ground that helps neither fast nor slow learners.”
While some might argue that encouraging students to graduate early deprives them of the opportunity to take more electives, there is growing evidence to suggest that having them focus on “the basics” would be a significant educational improvement. According to a report by the National Center for Educational Statistics at the United States Department of Education, so few high school graduates in the 1990s could read and write at minimum levels of proficiency that an astonishing 90 percent of colleges must offer remedial instruction and tutoring. Instead of trying to justify a fourth year of high school with an odd mixture of advance placement and eclectic non-core courses, perhaps its makes more sense to concentrate on fulfilling the real mission of secondary education and make sure that students are learning the basics when they need to — earlier.
2. Reduce State and Local Taxes
The appendix at the end of this paper shows what would happen if different Connecticut schools boards were to adopt a policy of rewarding those high school students who willingly graduate one year early. It lists all the high school districts in the state and shows the remarkable savings for taxpayers (before reserving for fixed costs, such as fuel oil and electricity) if 10 percent, 25 percent, or 50 percent of students agreed to graduate in three years with a scholarship equal to one third of the per pupil cost.
The calculations are based on the most recently available data from the Connecticut Department of Education on school enrollment and per pupil expenditures by district for the 2002-03 academic year. Given the generally rapid rate of inflation in the cost of educating Connecticut high school students (which shows no sign of abating), the question of how much of the taxpayer savings should be reduced for fixed costs ought to be viewed in light of the fact that the savings would be at least 15 percent higher in most cases, if 2004-05 data were available. In other words, for the sake of general argument, it is reasonable to assume that any need to take into account a reserve for fixed costs is offset by per pupil cost inflation — and, therefore, that the savings calculated for 2002- 2003 are very close to today’s net savings.
It is also worth noting that, due to the extremely wide variation in the distribution of Education Cost Sharing (ECS) dollars from state income tax revenues, many towns and districts effectively support their schools almost exclusively with local property taxes. What this means is that these towns and districts are in the enviable position of being able to unilaterally offer an early graduation reward without enabling legislation from Hartford. Of course, once it becomes clear how much all constituencies — students, their parents, and taxpayers without young children — would benefit from the proposed policy, it is hard to imagine the Legislature denying a similar opportunity to any Connecticut school district that requests it.
3. Stop the Boredom that Promotes Substance Abuse and Promiscuity
It doesn’t take an academic study to convince parents, teachers, and students what they already know in their hearts: that the senior year of high school is largely a waste of time. This is true for almost all seniors: those who are bright, those who are slow, and those in between.
Only part of the problem of this “wasted” year stems from the fact that students apply earlier to college than in times past and, once accepted, feel they have effectively finished high school long before graduation. In addition, today’s adolescents mature far more rapidly, both intellectually and physiologically, than they did when public education was invented two centuries ago.
The result is that we now confine adolescents to a secondary educational system that they have long outgrown by the age of 18. Indeed, about all a community gets for its investment in one of the highest cost years of public education is a valiant attempt by school guidance counselors to keep their most restless seniors out of trouble.
Unfortunately, even the best counselors are not always successful. By the time high school students reach their senior year, most can drive a car. The resulting combination of freedom and boredom is an open invitation for trouble — sometimes deadly trouble. In 2002, one in six high school seniors admitted to driving while high, making traffic crashes the leading cause of death for young people age 15 to 20. According to the non-partisan Centers for Disease Control and Prevention (CDC), 61.6 percent of high school students have had sex, much of it unprotected. The CDC also finds that 33 percent have been involved in violent incidents and 75 percent drink alcohol.
The tragedies implied by these statistics are not confined to any particular class, race, or district. In fact, the largest demand for illegal drugs in America comes from white middle-class suburbs, not from minority populations in poor urban areas; and more suburban high school seniors abuse alcohol and have sex with people with whom they have no romantic relationship than urban seniors. A recent report by New York’s Manhattan Institute, sponsored by the National Institute of Child Health and Human Development and other federal agencies, found that suburban public high school students have sex, drink, smoke, use illegal drugs, and engage in delinquent behavior at least as often as their urban counterparts and that all students engage in these behaviors more often than their parents realize.
Interestingly, the depressing statistics on self-destructive adolescent behavior do offer some hope. It turns out that most young people are quite capable of handling the availability of alcohol, drugs, and sex, if there is something meaningful at stake that can compete with these influences. Recognizing this fact, many school boards (particularly those in affluent communities) have attempted to keep juniors and seniors “occupied” with an ever expanding menu of sports, hobbies, and non-academic electives, effectively turning their high schools into playgrounds for oversized children. The flaw in this wellintentioned, if expensive, strategy is that American adolescents have an uncanny sense of hypocrisy. They know they are being deliberately distracted and that most high school electives are not on a caliber with a real college course or activity.
Psychological research strongly suggests that the most effective way we can help our young people to engage their latent talents and avoid harmful distractions is to encourage them to get out into the wider world and on with their lives at a younger age. In Botstein’s words, the current design of our high schools is “obsolete.” The reality we should no longer ignore is that they were designed two centuries ago for 15-to-18 year-old children and are now filled with young adults, who just happen to be the same age. In truth, the senior year can no longer fulfill the high academic expectations that taxpayers legitimately place on it. The four year curriculum is an increasingly inadequate solution to the problem of how to successfully motivate and educate contemporary adolescents. The best experience for many maturing teenagers is an alternative to the senior year of high school.
4. Make College More Affordable
At the very least, encouraging students to graduate early, earning something like a $5,000 scholarship in the process, accomplishes three things. First, it permits those students who are ready intellectually and emotionally to move on at the right time.
Second, it gives them a sense of real adult accomplishment, a reward for their hard work that is tangible and not at all gimmicky.
Third, it expands their options for future success by making expensive colleges more affordable, especially if they need financial aid beyond family resources. With the exception of a few elite colleges, even the most generous support packages from private and public universities have substantial “gaps,” which an early graduation scholarship could neatly fill.
For many the early graduation scholarship will mean nothing less than the opportunity to attend the school of their choice; for others it might just mean having more time to focus on extra-curricular activities or not having to go as deeply into debt. But at a time when college students are piling up more loans than ever before, 18 an early high school graduation scholarship is a substantial financial incentive for students of parents in nearly every income bracket.
It should be added that, if early graduation were to become widely popular in the United States, it would mean that millions of high school students would be giving up electives in lower grades to concentrate on core courses in reading, literature, math, and history. This would inevitably reduce college and university tuitions over the long run, because schools of higher education would not need to spend as much as they currently do on remedial tutoring and coursework.
5. Give Adolescents the Time Honored Chance to “Find Themselves”
Getting the intellectual boost of an accelerated education, earning a valuable scholarship, and saving himself or herself from the potentially self-destructive boredom of a wasted senior year are not the only ways that a student could benefit from the early graduation reward option. The graduating junior would also receive the priceless gift of time — an extra year that could be spent in any number of ways.
Some, of course, will want to go on to college right away. But others will now have the freedom to work for a year, apprentice in something like broadcasting or computer programming, volunteer for community service, or attend a community college for a semester or two before leaving home.
This freedom is no small gift. Many experts say that the level of college and professional school debt many students take on has deprived current and future generations of the important opportunity to pause and try something different before entering the worlds of work and family.
In 2003, the New York Times ran a front page story headlined “College Loans Rise, Swamping Graduates’ Dreams.” In it, the writer quotes William Wright-Swadel, director of career services at Harvard, who confirms that many college graduates have lost the freedom enjoyed by previous generations to take some time off from their career tracks and pursue an offbeat interest while they are still young.
The early graduation reward would be a way to preserve for those who need it the vanishing option to learn something unexpected about the world — and themselves. Canadian journalist Barbara Aggerholm surveyed a number of teenagers who took time off before college after the province of Ontario recently eliminated one year of high school and found that both they and their parents were quite pleased with the results.
6. Lower the Need for Costly New School Construction
Paying for the day-to-day operation of a school is not the only educational expense the community must assume. In areas where the student population is growing, districts find themselves repeatedly having to build or expand school facilities simply to accommodate an ever higher census. The real expense of such construction is often obscured by the practice of bonding it out over 20 or more years.
In addition, many states have “highest prevailing wage” laws, which require that workers on public buildings be paid far in excess of what might be available on the open market. As a result, even school boards in small districts of 4,000 to 5,000 households can end up committing taxpayers to $80 and $90 million in cumulative payouts of interest and principal for just one school project.
By trimming the high school census with a reward for voluntarily graduating early, school boards in growing communities can trim future requirements for expensive school construction.
7. Bring Well-Intentioned Citizens Together
It is hardly news that almost every community in America is divided on the issue of how to cope with the exploding cost of public education. Some believe the current system should continue to be subsidized no matter what the expense; others argue that public money ought to be used to send students to more cost-efficient private and religious secondary schools.
In the midst of all the debate and political posturing, two facts stand out. First, there are intelligent, caring people on both sides of the debate. Second, some of the most articulate spokespeople for both points of view enthusiastically support the idea of early graduation.
Certainly a cost-saving incentive to promote a reform that appeals to good people from all factions is worthy of serious consideration.
(See PDF for full list of Towns and savings.)

May 4, 2002

The Need for – and Feasibility of – a Voucher Program for Learning Disabled Children in Connecticut

Yankee Staff Policy Brief 0 Comments

By Lewis M. Andrews, Ph.D. Yankee Institute for Public Policy and
Matthew Ladner, Ph.D. Children First America
Revised May 4, 2002
The Need for New Options For Children With Disabilities
In 2001, the Thomas B. Fordham Foundation and the Progressive Policy Institute teamed to release a collection of studies titled Rethinking Special Education for a New Century, and the findings are staggering. “America’s program for youngsters with disabilities has developed infirmities, handicaps and special needs of its own,” Fordham and PPI concluded. “Merely adding dollars to the current program will not reform it.” Among the conclusions of the report: parents with learning disabled children are broadly dissatisfied with special education programs in the public schools … thousands of children have been labeled learning disabled merely because public schools have failed to teach them to read properly … and minority students are significantly more likely to be placed into special education programs in both white and non-white public school districts. A brief summary of some of the report’s findings will make the pathologies of the current special education system clear.
The number of students in special education nationwide has grown 65 percent since the inception of the Individuals with Disabilities Education Act (IDEA), to about 6.1 million in the 1999-2000 school year, or 8.2 percent of the overall student body. The largest growth has been in the percentage of children classified as learning disabled — which was 21 percent when the law was passed and 46 percent in 1998. The Economic Policy Institute estimates that 38 percent of each new tax dollar raised for public schools has been spent on special education.
Despite this massive investment of resources, many parents with children in public school special education programs express dissatisfaction with the level and types of services given to their children. “America’s special education program has an urgent special need of its own,” notes Thomas B. Fordham Foundation president Chester E. Finn. “It is, in many ways, broken.” Jay Matthews, education reporter for the Washington Post, agrees, noting that journalists (himself included) “have done a terrible job telling this story. Special education systems are often too confusing, too bureaucratic and too bound by privacy rules to yield much useful information.” What research is available, he adds, “suggests that the special education system has led to widespread, if well-intentioned, misuse of tax dollars and has failed to help kids ….”
Reading and Special Education
One of the most disturbing parts of the Fordham/PPI report lays out the argument that public schools could actually have prevented many special education students from acquiring their disabilities. Indeed, the case can be made that special education resources spent on children with preventable disabilities has crowded out needed services for more traditional, non-preventable disabilities.
A team of medical doctors led by Reid Lyon of the National Institute for Health found that many special education placements result from the failure to master basic reading skills at a young age. Children fall into three reading categories: those who learn to read before they begin school, those who learn relatively easily in school, and the 20 percent to 30 percent who need extra help. Dr. Lyon’s research demonstrates that intensive remedial reading instruction delivered at a young age could prevent 70% of learning disabilities. Nationwide, Dr. Lyon’s team estimates that nearly 2 million children have been classified as having learning disabilities that could have been either prevented or remediated with proper, rigorous early reading instruction. “From its inception as a category,” they conclude, “LD [learning disability] has served as a sociological sponge that attempts to wipe up general education’s spills and cleanse its ills” — all the while neglecting the fundamental needs of children with such traditional disabilities as Downs Syndrome, autism, blindness, and deafness.
Race and Special Education
Given the relationship between successful literacy training and disabilities, it is a sad fact that minorities are over represented in special education programs. Recent National Assessment of Educational Progress (NAEP) examinations, for example, found that 60% of African American 4th graders tested scored “below basic” on reading.
All public schools place minority children in special education programs at higher rates than white children; but according to the Fordham/Progressive Policy Institute study, predominantly white school districts label minority children as “learning disabled” at significantly higher rates than do other school districts. Why this should be can be explained by any number of perverse incentives, not the least of which is that special education students draw in additional state funding, and until recently, added federal dollars as well.
Florida’s McKay Scholarship Program
Overall, an ugly picture emerges where the failure of public schools to address the legitimate needs of children with non-preventable disabilities is compounded by the failure to teach many other children, especially many minority children, how to read properly at an early age. Children with preventable disabilities take resources away from children with non-preventable disabilities as well as from general education spending; and everyone ends up feeling shortchanged.
Obviously, public policy makers need to do two things: provide more educational freedom and flexibility to parents of learning disabled children, while at the same time creating incentives to encourage public schools to emphasize basic literacy in the early years. To see how this might be accomplished in Connecticut, consider the surprising evolution of the A+ Plan, the statewide voucher program adopted by the Florida legislature in 1999. Although initially designed as a general education reform, giving a voucher for private schooling to any student whose public school had failed to meet minimum academic standards in two of four years, the law did authorize a sweeping pilot program for learning disabled students in Sarasota County. Under this test project, the only requirement for a special needs child to transfer to a private school was that his parents express dissatisfaction over his progress at meeting the goals of his individualized education program (IEP).
So popular was the pilot program that just one year later state senator John McKay was able to pass an amendment to the original A+ Plan, allowing the Sarasota County provision to apply to the entire state. According to the new law, now known as the McKay Scholarship Program, private schools taking on a special needs child could recover from the government between $6,000 and $20,000, depending on the severity of the child’s disability. The only caveat was that any school wanting to enroll special education students supported by public money had to accept all applicants and not “cherry pick” among the disabled. In the school year 2000-2001, 105 private schools in thirty-six of Florida’s sixty-seven districts signed up to enroll more than 900 special education students. For the current academic year (2001-2002), Florida state officials estimate the number of learning disabled students receiving voucher assistance will quadruple to 4,000, while the number of participating schools will triple to over 300.
Why Such a Plan Could Work in Connecticut
1.) There is already considerable political support for some kind of voucher program in Connecticut, a state that is 43% Catholic and where the three diocese operate many of the low-cost private schools that would initially receive learning disabled children with vouchers. In the early 1990’s a voucher proposal nearly passed the House of Representatives in a tie vote, and the state’s current Governor, John Rowland, is on record as supporting public funding of private schooling for disadvantaged students.
2.) A voucher plan for learning disabled students could help alleviate the dissatisfaction behind a number of sweeping education equalization lawsuits, including Sheff v. O’Neill and Johnson v. Rowland.
3.) If you add the political clout of parents of learning disabled students to the forces already sympathetic to school choice, the momentum could be irresistible — especially if parents who wanted to home-school their learning disabled child would be eligible to receive a voucher payment for their efforts. In spite of the strong opposition of Florida’s teacher union, the McKay Scholarship Program sailed through that state’s legislature. Evidence suggests pivotal backing from the largest group of eligible families — those with moderately disabled children who, while continuing to be promoted with their classmates, were nevertheless floundering academically. “My child needed a choice, an alternative. (She) was lost in middle school,” says the mother of a scholarship recipient from the western part of the state. “She was held back early on, and the district did not want to keep holding her back, so even though she was not learning, she was moved along.” African American clergy from Florida’s cities, where the percentage of fourth graders unable to read can soar as high as sixty percent, were also outspoken supporters of the McKay Scholarship Program. (Interestingly, a similar alliance of middle class parents and minority clergy seems to have coalesced behind President Bush’s recently enacted No Child Left Behind education bill. While stripped of its initial tuition voucher proposal for mainstream schools, the legislation nevertheless retained its “supplemental services” provision, which makes parents at over 3,000 poorly performing schools nationwide eligible for federal funds for remedial tutoring at an independent school or even private company of their choice. Essentially a remedial education voucher program, it lets parents decide how and where the funds will be used.)
4.) Suburbanites, whose property taxes are swelling in response to special education mandates, would look favorably on a plan that gives parents of learning disabled students the freedom to go elsewhere. The McKay Scholarship Program limits the amount of a voucher to whatever the public school would have spent on the child, or the cost of private school tuition, whichever is less. When children enroll in schools with tuitions that are less than what the public school has been spending, the savings to suburban taxpayers can be enormous.
5.) The McKay Scholarship Program gives parents the opportunity to provide their disabled child with an appropriate education without having to sue their way out of their current situation. In Connecticut, such a program would create an enormous savings, both in terms of legal costs and emotional stress.
6.) Finally, it is difficult for Connecticut opponents of vouchers to argue that something like the McKay Scholarship Program violates separation of church and state. Public schools already contract out their most difficult-to-educate students (about 2% of the special education population) to private schools, the majority of which are run by religious institutions.
The Yankee Institute © 2002

January 1, 2002

Effects of Schools’ Racial Compositions on Educational Outcomes in Connecticut

Yankee Staff Policy Brief 0 Comments

By Thomas W. Bice

For tables, figures, graphs, and references see the attached PDF at the bottom of the page.

Executive Summary

Plaintiffs in the Sheff vs. O’Neill lawsuit currently before Connecticut’s courts seek to improve minority students’ educational outcomes by instituting magnet schools in the City of Hartford and opening schools in surrounding districts to inner-city Hartford students. The principal rationale underlying these demands holds that greater racial/ethnic balances in schools’ student bodies will bring about better academic performance among minority students. The study reported here was undertaken to test this presumption.

Using publicly available, aggregate data from 139 Connecticut high schools, the study estimates direct effects of schools’ racial compositions on tenth-graders’ scores on the four areas tested by the Connecticut Academic Performance Test (CAPT) — mathematics, science, reading, and writing. It does so using statistical methods that estimate these effects while adjusting test scores for effects of known determinants of academic performance.

The several analyses consistently find that schools’ racial compositions have no appreciable effect on academic performance among black and Hispanic students. The percentages of schools’ student bodies accounted for by white youths do not significantly influence any of the measures of academic performance investigated, including average Index scores, percentages of students meeting standards, and percentages of students who require remediation.

We conclude from our findings that the Sheff plaintiffs’ presumption that schools’ racial/ethnic compositions directly influence educational performance is incorrect.

From a brief survey of the education reform literature we also conclude that Sheff plaintiffs’ demand for magnet schools overlooks complexities encountered in urban school reform.

Introduction

In 1996 the Supreme Court of the State of Connecticut heard a suit in which plaintiffs sought to improve the educational circumstances and outcomes of the City of Hartford’s minority students, principally blacks and Latinos. The court ordered the State to effect a more balanced distribution of racial/ethnic groups among schools in the Hartford area and remanded the case to the Superior Court. In April of 2002 the Superior Court reopened the case. The plaintiffs’ preferred remedies are (1) to replace Hartford’s existing schools with magnet schools and (2) to compel public schools in Hartford’s surrounding suburbs to reserve portions of their capacities for inner-city students who might choose to attend them. The rationale underlying these proposed remedies presumes that attaining racial and ethnic balances within the region’s schools will have positive effects on the educational performance of minority students. This paper examines the tenability of that logic.

Although many studies find that schools’ racial/ethnic compositions are associated with educational outcomes, there is good reason to believe that this correlation is not a causal one. Based on their study of a national sample of more than 7,000 high school seniors, Chubb and Moe concluded that “[o]nce other influences of [academic] achievement are included in the [statistical] model, individual gains [in test scores] are virtually unaffected by the percentage of the student body that is black.” Grissmer and his associates conclude from their thorough study of trends in the so-called black-white test score gap that in the 1960s and 1970s school desegregation in the South narrowed the gap, but not elsewhere. Reflecting on these and other recent studies, Jencks and Philips reckon that “…racial mix does not seem to have much effect on changes in reading scores after the sixth grade or on math scores at any age, and that “…desegregation in northern schools might raise blacks’ reading scores today, but the gain would be modest.”

Studies conducted in various settings have shown that many interacting factors are implicated in educational performance. Among these are the quality of teachers and other school resources, parents’ encouragement of and involvement in their children’s education, and schools’ cultures, which in varying degrees either encourage or discourage academic performance. Schools’ racial/ethnic compositions are undoubtedly associated with some of these causative factors. An assessment of schools’ racial/ethnic compositions on academic performance therefore must take account of a web of interrelationships that includes contextual as well as other education-related factors. Accordingly, we estimate the direct relationship between students’ educational performance and the percentages of white students in their schools by adjusting for effects of known determinants of educational outcomes.

Figure 1 depicts the system of interrelationships that guides our analyses. The model indicates that towns’ and school districts’ socioeconomic situations affect education through two pathways. First, wealthier towns and districts and those with highly educated adults are likely to devote more funds to education. This expectation is depicted by the link of socioeconomic (SES) and Rural to indicators of schools’ resources (Resources). Second, we hypothesize that economically well-off communities have relatively higher proportions of parents who attach great importance to their children’s academic performance and translate that value into childrearing practices that reinforce schools’ educational missions. That effect is measured by Family.

Our model also recognizes the crucial of importance of what transpires within schools and among students. That effect is indicated by Culture, which attempts to tap the degree to which schools and their student bodies value academic objectives and translate this into supportive educational expectations and practices. Sociologists who coined the term “student culture” have found that schools’ and their student bodies’ cultures variously stress different values. Some place great emphasis upon athletics; others accentuate social ends; and others lay emphasis on academic performance. Our Culture relates primarily to this latter dimension.

Finally, the quality of teaching and administration in schools is a critically important factor. Regrettably, none of our indictors even approximates the type of data needed to capture these phenomena. Resources, as we will see, taps only structural dimensions of school quality. We do not suggest that our structural measures capture the more human and process-driven aspects of education. We therefore depict effects of these omitted factors with dashed lines leading to and emanating from Quality of Teaching & Administration.

The following section describes the methods employed in this study. Following this, we present quantitative results that address the associations implied by our conceptual model and the effects of schools’ racial compositions on black and Hispanic students’ educational performance. In the closing section, we spell out our findings’ implications for the Sheff case and for education more generally.

Data and Methods

Data

All of the data in this report are from published reports. Data pertaining to towns are from the Connecticut Department of Economic and Community Development, and information pertaining to schools and educational factors are from several reports issued by the Connecticut Department of Education.

Towns and School Districts

Data pertaining to towns and cities are from the Department of Economic and Community Development’s website. The Department publishes town profiles that include demographic, socioeconomic, business-related, and other types of information for all of Connecticut’s 169 towns. We assembled our community context information from those profiles.

For each town we recorded the following data, all of which we presume relate to towns’ socioeconomic environments.

● Population size (Pop)

● Population density (Density)

● Percent of dwelling units that are single-family (SHouse)

● Percent of dwellings that are owner-occupied (OwnOcc)

● Racial/ethnic composition: percent white (%White), percent black (%Black), and percent Hispanic (%Hisp)

● Per capita income (Income)

● Value of the town’s equalized grand list per capita (GrandList)

● Education levels of adults (persons 25 years of age and older): percent not graduating high school (NoHigh), percent with bachelors degrees or higher (Bach)

● Per capita number of books circulated annually by town libraries (Reading)

Our intent in gathering these data was to devise a concise yet reliable indicator of towns’ socioeconomic environments. To accomplish that we performed factor analyses on these data, which resulted in the two identifiable factors shown in Table 1. The coefficients in this table are factor loadings, which indicate the correlation of each variable with the underlying factors. For instance, Pop — our measure of towns’ population sizes — is highly negatively loaded onto the Rural factor, and has a negligible loading on SES. Variables in the upper panel of the table are components of the Rural factor; those in the lower panel are loaded on SES.

The Rural factor arrays towns along a continuum from rural through suburban to urban. The more rural communities thus have high scores on this factor, and large cities have low scores. For instance, the town of Hartland has the highest score on Rural. Hartland has about 2,000 residents who are scattered thinly (Density =60.5 people per square mile) and has values on other Rural variables that we associate with small-town Connecticut. Hartford lies at the other end of the Rural spectrum, closely positioned near Bridgeport, New Haven, and New London. Windsor Locks, Old Lyme, and Sharon fall in the mid region.

The SES factor arrays towns along a socioeconomic dimension that groups towns by levels of income, wealth, and education. Fairfield County towns are clustered at the high end of SES. New Canaan leads, followed closely by Darien, Weston, and Greenwich. Putnam, Griswold, and Killingly — all small towns — are at the low end of SES. Connecticut’s larger towns lie between the extremes. For instance, New London ranks 131st, Hartford 101st, and Bridgeport 97th from the top of SES.

Most regular/traditional school districts in Connecticut coincide with town borders. The sixteen regional school districts that encompass two or more towns are the exceptions. As we intend to analyze community contextual variables applied to school districts, we aggregated data from participating towns for each district. These district aggregations are the population weighted mean values on Rural and SES of the towns that participate in particular districts.

Schools

The Department of Education publishes on its website Strategic School Profiles for all of Connecticut’s public schools. These Profiles contain a wealth of quantitative data addressing demographic characteristics of schools’ student bodies, types of courses taken by the previous year’s graduating classes, scores on academic achievement tests, and other information. Our data pertaining to the state’s high schools are from these Profiles.

Our selection of variables was guided by the types of factors depicted in our conceptual model, namely Family, Culture, and Resources.

Family

We chose three variables to indicate families’ influences on their children’s education: school attendance, physical fitness, and dropout rates. Each of these variables in some degree stems from families’ decisions (or lack thereof). School attendance falls when parents permit truancy and when illnesses interfere with the exercise of normal activities. Physical fitness is to some extent a consequence of children’s diets and exercise regimes. Dropping out of school likewise bespeaks of lack of parental interest in education or lack of control over their children or both.

The Profiles list for each school its average school attendance percentage, the percentage of tenth graders who pass all four physical fitness tests administered by the school, and the cumulative four-year dropout rate for students in the previous year’s graduating class. We factor analyzed these data and created a Family factor from the resulting factor scores. Family factor loadings are 0.783 for school attendance, 0.682 for physical fitness, and -0.773 for dropout rates.

The Avon School District leads on Family followed closely by several Fairfield County towns. The low end of the continuum is occupied by schools located in the state’s larger towns. For instance, seven of the eight lowest ranked schools are in the Hartford, New Haven, New London, and Bridgeport school districts.

Culture

The data available to construct an indicator of schools’ culture are relatively satisfactory, at least for measuring their academic orientations. The Strategic School Profiles give for each school the types of courses taken by members of the previous year’s graduating class over their four high school years. These include the percentages who took four or more units in mathematics, three or more in science, four or more in social studies, two or more in the arts, and two or more in vocational education. Additionally, the Profiles supply information on the percentage of the previous year’s graduating class who took the Scholastic Achievement Test (SAT) —which is usually taken by students who aspire to go on to college — and the percentages of seniors who scored 600 or more on each of the SAT’s two sections (Quantitative and Verbal). The Profiles also give the school-wide percentages of students who were retained in grade during the previous year.

We estimated a graduating class-wide SAT score based on the assumption that no one who elected not to take the test would have achieved scores of 600 or higher had they participated. Our SAT Score indicator thus is simply the product of the percentage who take the test and the mean percentage of those who score 600 or more across the test’s two sections.

We factor analyzed these data and created a Culture factor score for each school from the results. The eight variables’ loadings on Culture are shown below. Four of the five subject matter areas have positive loadings, while vocational education is negatively associated with what might be termed an academically oriented culture. Failure rates’ (Retained in Grade) negative loading and the positive loadings associated with SAT participation and scores are consistent with that view.

We find that the state’s wealthier, suburban towns score high on this factor, while the inner city high schools are clustered at its low end. The Madison, Ridgefield, Westport, and Darien districts have the highest scores; Bridgeport, Hartford, and New London lie near the bottom of Culture’s distribution of districts.

School Resources

Strategic School Profiles supply numerous potential indicators of schools’ resources. We selected three types, namely, variables pertaining to (1) teacher quality, (2) library resources, and (3) technology.

Teacher quality is admittedly a difficult variable to measure, particularly when the available data pertain only to credentialing, as is the case with the Profiles. Our indicator of teacher quality is therefore admittedly crude, based as it is on only the total number of teachers per student, the number of teachers with masters degrees or higher and the number of teachers trained and qualified as mentors, assessors, or cooperating teachers. For each of the two credentialing variables we computed a per student ratio, that is, the number of credentialed teachers per student. In turn, we factor analyzed the three indicators in order to compute Teacher factor scores. The factor loadings are -0.921 for the ratio of students per teacher, 0.870 for masters level trained teachers per student, and 0.530 for mentor-trained teachers per student.

A Library factor was similarly constructed from data on the number of printed library volumes per student and the number of subscriptions per student.

Finally, we constructed a Technology factor from data describing the availability of electronic equipment. These include the percentages of classrooms that are wired for voice communications, are equipped for video presentations and data transmission, and that are connected to the Internet.

As we are not for present purposes interested in effects of particular intra-school features and believe that none of the factors we were able to construct is likely to be of much explanatory value, we created a super-factor based on a factor analysis of the three sets of factor scores. The individual loadings of Teacher, Library, and Technology on his so-called Resources factor are, respectively, 0.848, 0.873, and 0.252.

The alignment of schools on the resulting Resources factor is not easily summarized. At the high end are such diverse schools as some of those in Fairfield County and other relatively wealthy districts. At the low end one finds schools in the Bristol and West Hartford districts.

Educational Outcomes: CAPT Scores

The CAPT is a state-mandated examination that is administered annually to tenth graders. The test covers four areas, namely, mathematics, science, reading, and writing. The Department of Education reports three versions of scores for each of these four skill areas: (1) percentages of students scoring in each of four levels (ranging from “requiring remediation” to “meeting standards”), (2) average “Index Scores,” and (3) scale scores.

We analyze each of the four CAPT area scores separately, examining for each the Index scores, the percentages of students meeting standards, and the percentages requiring remediation.

Selection of Schools

The Department of Education’s Strategic School Profiles list 192 public academic institutions that provide high school-level education categorized as shown in Table 2. As the Sheff case focuses on conventional schools, we confine our analyses to regular/traditional and magnet schools. Of these 162 institutions, complete data from the various sources we employed were available for 139 schools.

The loss of some schools resulted from the unavailability of CAPT scores. The Department of Education does not report results for subgroups of ten or fewer students. Therefore no data are available for schools that have fewer than that number of tenth graders. As the overwhelming majority of students in Connecticut schools are white, this policy results in relatively sparse data for minority groups. Table 3 shows the availability of CAPT scores among the 139 schools in our analysis.

Our 139 schools yield 240 observed sets of aggregate CAPT scores. As percentages of eligible children for whom data are reported for each of the areas differ among schools, this number varies slightly among CAPT areas.

Racial Composition

The principal policy-related question in our analysis pertains to the effect of schools’ racial/ethnic compositions on educational outcomes, in this case CAPT scores. This factor is measured by two variables: (1) a dummy variable that measures average differences in CAPT scores among white, black, and Hispanic students and (2) the racial compositions of schools’ student bodies.

Black & Hispanic

A dummy variable is employed in statistical analyses to capture differences among categorical groups. A dummy variable is defined by k-1 categories, where k is the number of groups. The omitted category is the reference group to which the other categories are compared.

In our analyses, we employ white students as the reference group and measure differences with Black, which indicates the average difference between white students’ CAPT scores and those of black students and Hispanic, which measures the corresponding difference for Hispanic students.

Racial Composition

Given the Sheff plaintiffs’ logic, the definition of the variable measuring the racial compositions of schools deserves special attention.

The Sheff argument suggests that schools’ racial compositions affect only minority students’ educational performance. In effect, Sheff hypothesizes an interaction effect in which schools’ racial compositions will affect minority students’ educational outcomes but not those of white students. Accordingly, measuring schools’ compositions simply by the percentages of schools’ student bodies that are white (%White) does not provide an appropriate estimate of racial composition’s effects on educational outcomes.

Scatter plots of CAPT scores across schools’ racial compositions demonstrate that patterns of CAPT scores differ among white, black, and Hispanic students. Figure 2 shows that white students’ CAPT have relatively little variance overall, and scores are not highly correlated with the percentages of their student bodies accounted for by white students (%White). The best fitting linear line through these CAPT scores is

Y = 71.313 +0.024X,

where Y refers to the CAPT score and X to %White. That line accounts for only 13.1 percent of the variance in CAPT scores.

The scatters plot of black and Hispanic students’ CAPT scores across %White differ from that for white students, and %White has a greater effect. Figure 3 shows that black students’ scores are distributed rather evenly across %White with a tendency for higher scores to be found among schools with the highest percentages of white students. The best-fitting linear line is:

Y = 41.579 + 0.158X

This statistical model explains 16.4 percent of the total variance in black students’ CAPT scores and is thus a slightly better fit than that for white student’s scores.

The scatters plot of Hispanic students’ CAPT scores across %White (Figure 4) also indicates a slight tendency for CAPT scores to be higher among schools with higher percentages of white students. However, the best-fitting line through these points accounts for only ten percent of the variance in CAPT scores and bends slightly downward among schools with the highest percentages of white students:

Y = 39.039 + 0.609X – 0.005X

Taken together, these three scatter plots and statistical models of best-fitting lines clearly indicate that %White does not have a consistent effect across white students and black students. We therefore indicate schools’ racial compositions in our analyses with three variables, White*%White, Black*%White, and Hispanic*%White. White*%White is assigned the value of zero for all black and Hispanic students’ CAPT scores and for white students takes on the value of the percentages of schools’ student bodies that are accounted for by white students. Black*%White is assigned the value of zero for all white and Hispanic students’ CAPT scores and for black students is assigned the value of the percentages of schools’ student bodies that are accounted for by white students for all others. Hispanic*%White likewise is zero for black and white students’ CAPT scores and %White for Hispanic students.

Statistical Methods

Our analytic objectives dictate the use of multivariate statistical estimation models. Recognizing that the niceties of such approaches might not be accessible to the lay reader, we describe its features below in order to elucidate some of the statistical jargon that appears in our discussion of findings.

The models we estimate attempt to test which of two hypotheses regarding the effect of schools’ racial compositions on CAPT scores is more tenable, that of the Sheff plaintiffs or that we pose as an alternative. This analytical objective focuses attention on our estimates of effects of five variables (Black, Hispanic, White*%White, Black*%White, and Hispanic*%White) and particularly the latter three.

Multivariate Analysis

The purpose of multivariate analysis is to estimate the individual effect of each of a set of predictor variables on a dependent variable when effects of all other predictor variables included in the statistical model are adjusted (or “held constant”). We use a statistical procedure known as multivariate regression analysis, whose statistical model is

Y = c + b1X1 + b2X2 + … + bkXk + e,

where Y denotes an observed value of the “dependent variable,” an observed CAPT score. Each X stands for the value of an observed predictor variable. The c term is an unknown “constant” that the model estimates. Each b (“regression coefficient”) indicates the model’s estimate of its corresponding predictor variable’s effect on Y when effects of all other Xs are adjusted. The e term is the “error term,” which measures effects of all other potential Xs that are not included in the model and measurement error in the included ones. In a linear statistical model such as we employ, the sum of all these effects equals the predicted CAPT score.

Results from applying this model to our data yield quantitative estimates of the unknowns, the c, b and e terms. The overall fit of the model to the underlying data is indicated the size of e. This is expressed as 1-R2, where R2 equals the percentage of the observed variance in Y “explained” by the entire model. This ranges from zero percent (when the model’s predictor variables in combination explain nothing) to 100 percent (when the model perfectly fits the underlying observed data).

The constant term c estimates the value of Y when all predictor variable values equal zero. Each b estimates the independent effect of its corresponding X score. These range from zero, which indicates no effect, to unbounded positive and negative values. Positively signed values indicate that increases in the X variable are associated with higher Y (CAPT) scores; negatively signed values indicate that increases in the X variable are associated with lower Y (CAPT) scores. More specifically, a b’s quantitative value indicates the amount that Y changes when X changes by one unit and when effects of all other Xs are adjusted. Thus, a b equal to, say, 0.50 indicates that a one-unit increase in X brings about a 0.50 increase in Y (CAPT score).

Statistical Hypotheses

Two competing hypotheses are at risk in our analyses. The Sheff hypothesis, in effect, states that [insert figure].

In words, the variables Black, Hispanic, and White*%White will have no effect on CAPT scores when effects other predictor variables are adjusted; and Black*%White and Hispanic*%White will have positive effects.

Our competing hypothesis holds that none of these variables will significantly affect CAPT scores when effects of other predictors are adjusted. Rather, we expect that other predictors, which we regard as being true determinants of educational outcomes, will account for all of the variance in CAPT scores that our predictor variables are able to explain.

Statistical Significance

Finally, a word on statistical significance. When samples of observed data are selected from larger universes of data, statistical analyses infer population parameters from statistics computed on sample data. Sample statistics never equal corresponding parameters. Statistical theory, however, permits us to estimate for each sample statistic a range within which the corresponding parameter is likely to fall. Ranges can be constructed for various levels of confidence. It follows that greater confidence is associated with wider ranges, and vice versa. Conventionally, analysts employ 95 percent confidence as the point that distinguishes “statistically significant” findings from “statistically insignificant” ones. The former are denoted by “p < 0.05,” that is, the particular estimated parameter range would be expected to include zero in five percent of all possible samples of a particular size drawn from a specified universe of data in which the parameter is greater than zero. This estimate is popularly described as being the effect of chance variation; more strictly it measures “sampling error”.

As our observed data were not selected by any known sampling method from a larger universe of data, conventional interpretations cannot be assigned to estimated tests of statistical significance. Nevertheless, we report “p-values” and use them as rough indicators of statistical significance. In all tables reporting regression results “*” indicates that the coefficient is statistically significant at the 90 percent level of confidence and “**” at the 95 percent level. We are not slavishly attached to this criterion, however. We consider these results along with regression coefficients’ stability across the various specifications of our statistical model and with the substantive interpretations that models suggest.

Results

Descriptive Findings

As Figure 4 shows, all groups’ educational performance is associated with the racial
compositions of the schools they attend. All groups’ CAPT scores increase across %White. However, white students’ average CAPT scores are uniformly higher than those of black and Hispanic youths at all levels of %White.

The findings regarding black and Hispanic students would appear to support Sheff plaintiffs’ assumption that alteration of the racial compositions of schools affects minority groups’ educational performance. However, the fact that white students’ scores are associated with the racial compositions of their schools is inexplicable by that logic. Were we to interpret %White effects causally, we would conclude that increasing the numbers of white students in schools would improve white students’ academic performance, or the opposite that increasing numbers of minority students would diminish white students’ educational outcomes. The former view, we believe is untenable; the latter is politically explosive.

A more reasonable interpretation of the correlation between %White and CAPT scores is that schools’ racial compositions are associated with other factors that cause variations in educational outcomes. The multivariate analyses that follow investigate that possibility.

Correlations of %White with other causative factors specified by our model and with indicators of educational performance are shown in Tables 4. These zero-order correlations show that %White is positively associated with all hypothesized determinants of educational outcomes and with the mean CAPT scores. In turn, groups’ average CAPT scores are correlated with all hypothesized determinants.

Overall, the zero-order correlation coefficients in Table 4 lend support to our conceptual
model. All hypothesized causative factors are associated with CAPT scores, and community level factors are closely related to family and educational variables. They also indicate that the prevalences of education-enhancing and favorable educational outcomes are greater in Connecticut’s more rural and wealthier communities than in its less wealthy urban areas.

We also find that %White is correlated not only with educational outcome indicators but with hypothesized causative factors as well. This suggests that the %White-CAPT association might merely be an artifact of %White‘s covariation with the causative factors. Tests of this suspicion require multivariate analyses to which we now turn.

Estimation of Effects

Our assessment of causative factors implicated in educational outcomes proceeds stepwise through our model. We begin by estimating effects of White, White*%White, and Black*%White alone. We then successively introduce community variables (Rural and SES) and then family and educational variables (Family, Culture, and Resources). Of particular interest in these analyses are coefficients associated with White*%White, Black*%White, and Hispanic*%White. If our logic holds, these variables’ estimated effects will diminish as other predictor variables are introduced.

Table 5 shows the regression coefficients estimated by the four specifications of our statistical model. Model I gives estimates of regression coefficients associated with Black, Hispanic, White*%White, Black*%White and Hispanic*%White when they alone are regressed onto CAPT Math Index scores. These data indicate that the aggregate white students’ CAPT Math Index scores are on average more than thirty-seven points higher than those of black students and thirty-five points higher than those of Hispanic students after accounting for schools’ racial compositions. Regression coefficients associated with White*%White, Black*%White, and Hispanic*%White show that increasing %White boosts aggregate CAPT Math Index scores for all students. A ten percent increase in %White raises white students’ scores by about 1.4 points, those of black students by 2.7 points, and those of Hispanic students by about 3.3 points.

Already, our findings lead us to doubt the Sheff logic. The model’s R2 of 83 percent indicates that this specification explains a relatively large portion of the observed variance in CAPT scores. However, the Black and Hispanic coefficients remain large and statistically significant, and the White*%White coefficient is statistically significant. White students’ average CAPT Math Index scores are considerably higher than those of minority students regardless of schools’ racial compositions. Moreover, increasing percentages of white students in schools’ student bodies increase aggregate performance among all students, whites as well as minority groups. For instance, the model’s predicted CAPT Math Index score for white students in a school with twenty percent white students is 70. In the same school, the predicted CAPT score for black students is about 34, and that for Hispanic students is 38. In a school whose white students comprise ninety percent of the student body, predicted aggregate CAPT scores for white students, black students, and Hispanic students are, respectively, about 80, 53, and 60.

Model II adds community variables, Rural and SES. This leads to a slightly better statistical fit with the data (R2 =88.3%). Rural and SES raise CAPT Math Index scores. The effect of racial composition on scores remains positive and statistically significant for black students and Hispanic students, while that effect among white students is virtually zero.

Model III estimates effects of racial/ethnic variables in conjunction with family and school level variables. In this specification the average white-black (Black) and white-Hispanic (Hispanic) differences remain, as do effects of schools’ racial compositions (White*%White, Black*%White, & Hispanic*%White). Coefficients associated with all of the other predictors in Model III are consistent with our conceptual model. All are positively signed, and all but one (Resources) are statistically significant.

Finally, Model IV includes all predictor variables. The absolute values of the coefficients associated with indicators of racial composition are virtually zero among white students and black students and is small but statistically significant among Hispanic students. We conclude from these results that schools’ percentages of white students have no effect on educational outcomes as measured by CAPT Math Index scores among white students and black students and perhaps a trivial effect on those of Hispanic students.

In addition to overall averages as measured by Index scores, we are interested in extreme scores as well, namely, those in the group who meet standards and those whose scores are so low as to indicate needs for special intervention.

Table 6 gives parameter estimates for these math outcomes based on the full model. In both cases, estimates of schools’ racial compositions on minority students’ CAPT Math scores are near zero and not statistically significant.

Tables 7 through 9 show results from analyses of CAPT Science, Reading, and Writing scores. In each case, results indicate that, when effects of other pertinent factors are adjusted, racial compositions of schools have no effect on minority students’ CAPT scores.

Summary and Conclusions

Summary

This paper was occasioned by the Sheff vs. O’Neil court case in which plaintiffs presume that establishing more racially and ethnically balanced student bodies will lead to improved educational performance among minority group students, principally black and Hispanic youths.

The study reported here was undertaken to test the racial/ethnic composition effect implied by Sheff. We examined this hypothesized effect among the Connecticut’s tenth-grade students for whom aggregate scores on their Connecticut Academic Performance Test (CAPT) are reported. We posited a conceptual model of educational outcomes that draws together influences of students’ communities, families, and intra-school factors. Using multivariate regression analyses whose specifications were defined by this conceptual model, we compared white, black, and Hispanic students’ academic performance across the 139 Connecticut schools for which we could assemble complete data sets. Each statistical model included indicators of schools’ racial mixes, which permitted us to estimate these variables’ direct effects after adjusting for effects of our conceptual model’s hypothesized determinants’ of academic performance.

Our principal findings are summarized as follows.

● Based on conventional quantitative criteria, our statistical models fit the observed data very well.

● Hypothesized determinants of educational performance pertaining to influences of communities’ socioeconomic features and of families and schools’ academic cultures are rather consistently associated with academic performance.

● Once effects of these factors are adjusted, schools’ racial compositions have no effect on tenth-graders’ educational outcomes.

Limitations

While our analyses confidently reject the notion that altering schools’ racial/ethnic compositions will improve minority groups’ academic performance, we note that the study suffers from limitations. First, our findings are based on non-experimental observations. The ideal design for estimating causal effects would observe changes in academic performance among students randomly assigned to various schools. Such a design is both infeasible and undesirable, however. Moreover, as our intent was to examine a single, specific question, the statewide scope of the available non-experimental data permits broader generalization.

Second, as we investigated only tenth-graders, we cannot assume that our results apply to other student cohorts. We therefore suggest that additional research be carried out on test scores (e.g., Connecticut Mastery Test [CMT] of elementary school students.

Third, our analyses are based exclusively on readily available aggregated data, both test scores and predictor variables. In particular, Rural and SES apply district-wide variables to individual students, and Family and Culture apply school-level measures to white students, black and Hispanic students alike. Measuring individual differences among students on these dimensions and other relevant dimensions most certainly would add to our study’s sensitivity. Additionally, analyses based on individual-level data that more thoroughly measure family and cultural influences would provide policy makers with more direction as to scope and content of needed reforms. Such investigations certainly should focus on the quality of schools’ teachers and administration, factors that publicly available information does not address.

Conclusions

Our analyses consistently yield a troubling finding that deserves particular attention. In all statistical models that estimate white-black and white-Hispanic achievement differences, we find that, on average, white students outperform both black students and Hispanic students even with effects of other predictors held constant. Indeed, the average differences in whiteblack and white-Hispanic aggregate test scores remain almost unchanged from the mean difference observed when no other variables are considered. We cannot estimate precise extents of persisting white-black and white-Hispanic differences from the data at hand. On the other hand, other studies report gaps of similar magnitudes between white students’ performance and that of black students, which endure even when many determinants are adjusted.

These enduring test score gaps between white and minority students point to schools themselves and to the orientations, encouragement, and emotional intelligence that students bring to schools from their homes. Sheff plaintiffs’ demand for replacing Hartford’s existing inner-city schools with magnet schools takes a step in this direction, but a woefully incomplete one. The history of school reform in the United States is replete with instances of “single bullet reforms” that regrettably are often short lived and ineffective. Magnet schools might improve educational outcomes in some settings. The same might be said for charter schools, contracted schools, and other alternatives to prevailing arrangements.

But mere generalities do not suffice, for they mask considerable diversity in the particulars that actually effect outcomes. Beneath brand names lies a host of design decisions that involve far-reaching considerations of schools’ missions and management as well as their modes of accountability and relationships to other community resources. In that regard, one might reasonably question the basic tenant of the proposed Sheff remedy, which envisions students traveling from suburban Hartford towns to attend inner-city Hartford magnet schools. Experience elsewhere shows that such arrangements often fail to attract students from suburban communities, for parents generally prefer sending their children to local schools. This has been found in Minnesota, the first state to adopt such reforms, and in Massachusetts, where, as of the mid-1990’s, fewer than twenty five percent of the state’s schools, and none of Boston’s suburban communities, participated in the statewide program.

At least in broad outline, considerable agreement exists among educational experts as to where attention should be focused. Instead of mandating a general type of reform, Connecticut’s policy makers should initiate a planning process that takes what is known to work and adapts these lessons to Hartford’s particular circumstances. Such planning and design must then be followed by a long-term political commitment to oversee, support, and continually adjust whatever reforms are adopted. As Hill and Celio note,

[a]ny city’s reform can take a decade. That is a tragically long time, given the costs to children. However, unless education reform is taken seriously, as an effort requiring serious thinking, testing, careful use of evidence, and continuous refinement, America’s urban public schools are likely to be no better off in ten years than they are now.

Our study’s findings reject that part of Sheff that expects redistributions of students among schools to bring about better academic performance among minority students. Accumulated knowledge and experience in urban education reform likewise eschew a simplistic embracing of the magnet school (or any other reform) label. The lawsuit is thus without substantive merit. Indeed, the courts are inappropriate venues for the sorts of hard thinking and political will that are required to bring about better education for Hartford’s children.

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